Add weak timings

This commit is contained in:
Paul Brinkmeier 2024-03-11 01:45:18 +01:00
parent 79227e93d9
commit dac08095c4
8 changed files with 91 additions and 1 deletions

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@ -0,0 +1,9 @@
nodes tasks mean_time std_time efficiency efficiency_error
1 1 41.98463099999999 1.4067920862965122 1.0 0.023219381860496473
1 2 49.85189340000001 1.7669363566083227 0.8421872899214694 0.020685165974491628
1 4 59.9694977 2.209151778903949 0.7000997608822725 0.01787171173813342
2 8 72.810012625 0.5538313058789631 0.5766326565034021 0.003039461920431096
4 16 84.718001525 5.20969191162485 0.4955809892140865 0.021118450727088397
8 32 87.22569569999999 1.7018797711775082 0.4813332890390463 0.0065079080866405825
16 64 85.36740952500001 1.0197522041876155 0.49181099946232654 0.004071100890302765
32 128 87.5995021046875 0.8707125543332932 0.47927933368645675 0.003301208459097849
1 nodes tasks mean_time std_time efficiency efficiency_error
2 1 1 41.98463099999999 1.4067920862965122 1.0 0.023219381860496473
3 1 2 49.85189340000001 1.7669363566083227 0.8421872899214694 0.020685165974491628
4 1 4 59.9694977 2.209151778903949 0.7000997608822725 0.01787171173813342
5 2 8 72.810012625 0.5538313058789631 0.5766326565034021 0.003039461920431096
6 4 16 84.718001525 5.20969191162485 0.4955809892140865 0.021118450727088397
7 8 32 87.22569569999999 1.7018797711775082 0.4813332890390463 0.0065079080866405825
8 16 64 85.36740952500001 1.0197522041876155 0.49181099946232654 0.004071100890302765
9 32 128 87.5995021046875 0.8707125543332932 0.47927933368645675 0.003301208459097849

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@ -0,0 +1,10 @@
nodes tasks mean_time std_time efficiency efficiency_error
1 48 234.09125610833334 4.9756238110995765 1.0 0.013886639526655382
2 96 234.09269640000002 1.9886350551995884 0.9999938473447108 0.005550081636855162
4 192 239.06532950520833 1.8931447841474947 0.9791936647310181 0.005066063671757703
8 384 241.32357499479167 0.977728668984766 0.9700306160033705 0.0025676679349660694
16 768 260.8008324059896 12.802824235961744 0.8975863073317291 0.028787758154736998
32 1536 266.59983470546877 13.970338204797093 0.8780622702446538 0.03006125980502309
64 3072 281.61153985800786 25.95560834859075 0.8312559074332151 0.05005532970709546
128 6144 293.4177162058594 10.8076489888669 0.7978088683101088 0.019198998510810975
256 12288 310.9775802693196 14.459893325743863 0.7527592693518308 0.022867934404056486
1 nodes tasks mean_time std_time efficiency efficiency_error
2 1 48 234.09125610833334 4.9756238110995765 1.0 0.013886639526655382
3 2 96 234.09269640000002 1.9886350551995884 0.9999938473447108 0.005550081636855162
4 4 192 239.06532950520833 1.8931447841474947 0.9791936647310181 0.005066063671757703
5 8 384 241.32357499479167 0.977728668984766 0.9700306160033705 0.0025676679349660694
6 16 768 260.8008324059896 12.802824235961744 0.8975863073317291 0.028787758154736998
7 32 1536 266.59983470546877 13.970338204797093 0.8780622702446538 0.03006125980502309
8 64 3072 281.61153985800786 25.95560834859075 0.8312559074332151 0.05005532970709546
9 128 6144 293.4177162058594 10.8076489888669 0.7978088683101088 0.019198998510810975
10 256 12288 310.9775802693196 14.459893325743863 0.7527592693518308 0.022867934404056486

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@ -0,0 +1,9 @@
nodes tasks mean_time std_time efficiency efficiency_error
1 1 60.658062599999994 1.8711952545625232 1.0 0.021376748626269895
1 2 80.6903592 1.1554429061827625 0.751738661240214 0.007459415624087278
1 4 89.01234124999999 1.3979557323025515 0.6814567704677693 0.00741639040919915
2 8 101.357940575 4.784240687736861 0.5984539766286584 0.01957478845779047
4 16 106.2530252 1.5044057675724636 0.5708831582519497 0.005601211794070455
8 32 113.70197445 2.069642901549501 0.5334829310873062 0.006729131548114211
16 64 119.22770070624999 0.7600051865549382 0.5087581345667959 0.00224730403456563
32 128 121.8124414140625 0.5170666166834136 0.4979627852118346 0.0014647476739746731
1 nodes tasks mean_time std_time efficiency efficiency_error
2 1 1 60.658062599999994 1.8711952545625232 1.0 0.021376748626269895
3 1 2 80.6903592 1.1554429061827625 0.751738661240214 0.007459415624087278
4 1 4 89.01234124999999 1.3979557323025515 0.6814567704677693 0.00741639040919915
5 2 8 101.357940575 4.784240687736861 0.5984539766286584 0.01957478845779047
6 4 16 106.2530252 1.5044057675724636 0.5708831582519497 0.005601211794070455
7 8 32 113.70197445 2.069642901549501 0.5334829310873062 0.006729131548114211
8 16 64 119.22770070624999 0.7600051865549382 0.5087581345667959 0.00224730403456563
9 32 128 121.8124414140625 0.5170666166834136 0.4979627852118346 0.0014647476739746731

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@ -129,6 +129,42 @@ def make_cpu_ex(x: int, y: int, z: int) -> Experiment:
)
def make_gpu_ex(x: int, y: int, z: int) -> Experiment:
num_blocks = x * y * z
gpus_per_node = num_blocks if num_blocks <= 4 else 4
num_nodes = 1 if num_blocks <= 4 else num_blocks // 4
return Experiment(
job_name=f"weak-gpu-{x:02}-{y:02}-{z:02}",
account="cellsinsilico",
partition="gpus",
extra_sbatch_line=f"#SBATCH --gres=gpu:{gpus_per_node}",
nastja_binary_path="/p/project/cellsinsilico/paulslustigebude/nastja/build-cuda/nastja",
nodes=num_nodes,
tasks=num_blocks,
num_blocks=(x, y, z),
domain_scale=(x, y, z),
)
def make_booster_ex(x: int, y: int, z: int) -> Experiment:
num_blocks = x * y * z
gpus_per_node = num_blocks if num_blocks <= 4 else 4
num_nodes = 1 if num_blocks <= 4 else num_blocks // 4
return Experiment(
job_name=f"weak-booster-{x:02}-{y:02}-{z:02}",
account="hkf6",
partition="booster",
extra_sbatch_line=f"#SBATCH --gres=gpu:{gpus_per_node}",
nastja_binary_path="/p/project/cellsinsilico/paulslustigebude/nastja/build-cuda/nastja",
nodes=num_nodes,
tasks=num_blocks,
num_blocks=(x, y, z),
domain_scale=(x, y, z),
)
experiments = [
make_cpu_ex(4, 4, 3),
make_cpu_ex(4, 4, 6),
@ -138,6 +174,25 @@ experiments = [
make_cpu_ex(8, 8, 24),
make_cpu_ex(8, 16, 24),
make_cpu_ex(16, 16, 24),
make_cpu_ex(16, 16, 48),
make_gpu_ex(1, 1, 1),
make_gpu_ex(1, 1, 2),
make_gpu_ex(1, 2, 2),
make_gpu_ex(2, 2, 2),
make_gpu_ex(2, 2, 4),
make_gpu_ex(2, 4, 4),
make_gpu_ex(4, 4, 4),
make_gpu_ex(4, 4, 8),
make_booster_ex(1, 1, 1),
make_booster_ex(1, 1, 2),
make_booster_ex(1, 2, 2),
make_booster_ex(2, 2, 2),
make_booster_ex(2, 2, 4),
make_booster_ex(2, 4, 4),
make_booster_ex(4, 4, 4),
make_booster_ex(4, 4, 8),
]
if __name__ == "__main__":

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@ -12,9 +12,13 @@ def show_seconds(s: float) -> str:
if __name__ == '__main__':
p = argparse.ArgumentParser(description="Make a latex table from a timings tsv")
p.add_argument("timingfile")
p.add_argument("--weak", action="store_true")
args = p.parse_args()
df = pandas.read_csv(args.timingfile, sep="\t")
for i in range(len(df)):
print(f"{df['nodes'][i]} & {df['tasks'][i]} & {show_seconds(df['mean_time'][i])} & {show_seconds(df['std_time'][i])} & {df['speedup'][i]:.02f} & {df['speedup_error'][i]:.02f} \\\\")
if not args.weak:
print(f"{df['nodes'][i]} & {df['tasks'][i]} & {show_seconds(df['mean_time'][i])} & {show_seconds(df['std_time'][i])} & {df['speedup'][i]:.02f} & {df['speedup_error'][i]:.02f} \\\\")
else:
print(f"{df['nodes'][i]} & {df['tasks'][i]} & {show_seconds(df['mean_time'][i])} & {show_seconds(df['std_time'][i])} & {df['efficiency'][i]:.02f} & {df['efficiency_error'][i]:.02f} \\\\")